Text analytics for uncovering untapped ideas at the intersection of learning design and learning analytics: Critical interpretative synthesis

Abstract

AbstractBackgroundLearning analytics (LA) collects, analyses, and reports data from the learning environment, to provide evidence of the effects of a particular learning design. Learning design (LD) outlines the conceptual framework for a meaningful interpretation of Learning analytics data.ObjectivesThe study aims to identify the most relevant concepts at the intersection of learning design and learning analytics, how these concepts are integrated into more general thematic areas, and the implications for the research and practice of the learning design and learning analytics synergy.MethodsTo this end, the study employs a critical interpretive synthesis (CIS) of the selected papers, and complements it with elements of systematic literature review as well as qualitative content analysis and text analytics that employ machine learning and language technology.Results and conclusionsThe most important themes identified are ‘analytics’, ‘learning’, ‘data’, ‘tools’, ‘research’, ‘framework’, ‘informed’, ‘model‐driven’, ‘participatory’, ‘technique’, ‘impact’, insight’, and ‘findings'. The text analytics detected two topic rarely explicitly discussed in the literature: ‘evidence‐informed instructional design approaches' and ‘design‐based research’. Future research should attempt a holistic perspective towards the LD and LA synergy considering evidence‐informed instructional design approaches as part of a design‐based research methodology that implements evidence‐based teachers' practice and research‐based findings.